142 lines
5.6 KiB
Python
142 lines
5.6 KiB
Python
"""
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FILE: app/core/chunking/chunking_strategies.py
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DESCRIPTION: Korrigierte Splitting-Strategien für Mindnet v3.3.3.
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- Fix: Erhalt von Überschriften im Chunk-Text.
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- Fix: Atomares Buffering (Blöcke fallen als Ganzes in den nächsten Chunk).
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- Fix: Korrekte Zuordnung von Sektions-Metadaten.
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"""
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from typing import List, Dict, Any, Optional
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from .chunking_models import RawBlock, Chunk
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from .chunking_utils import estimate_tokens
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from .chunking_parser import split_sentences
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def _create_context_win(doc_title: str, sec_title: Optional[str], text: str) -> str:
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"""Baut den Breadcrumb-Kontext für das Embedding-Fenster."""
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parts = []
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if doc_title: parts.append(doc_title)
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if sec_title and sec_title != doc_title: parts.append(sec_title)
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prefix = " > ".join(parts)
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return f"{prefix}\n{text}".strip() if prefix else text
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def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]:
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"""
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Splittet Text basierend auf Markdown-Überschriften mit atomarem Block-Erhalt.
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"""
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strict = config.get("strict_heading_split", False)
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target = config.get("target", 400)
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max_tokens = config.get("max", 600)
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split_level = config.get("split_level", 2)
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overlap = sum(config.get("overlap", (50, 80))) // 2
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chunks: List[Chunk] = []
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buf: List[RawBlock] = []
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cur_tokens = 0
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def _add_to_chunks(txt, title, path):
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idx = len(chunks)
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win = _create_context_win(doc_title, title, txt)
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chunks.append(Chunk(
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id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx,
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text=txt, window=win, token_count=estimate_tokens(txt),
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section_title=title, section_path=path,
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neighbors_prev=None, neighbors_next=None
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))
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def _flush():
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nonlocal buf, cur_tokens
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if not buf: return
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# Metadaten stammen immer vom ersten Block im Puffer (meist die Überschrift)
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main_title = buf[0].section_title
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main_path = buf[0].section_path
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full_text = "\n\n".join([b.text for b in buf])
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# Falls der gesamte Puffer in einen Chunk passt
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if estimate_tokens(full_text) <= max_tokens:
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_add_to_chunks(full_text, main_title, main_path)
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else:
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# Nur wenn ein einzelner Abschnitt größer als 'max' ist, wird intern gesplittet
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sents = split_sentences(full_text)
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cur_sents = []; sub_len = 0
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for s in sents:
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slen = estimate_tokens(s)
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if sub_len + slen > target and cur_sents:
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_add_to_chunks(" ".join(cur_sents), main_title, main_path)
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ov_s = []; ov_l = 0
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for os in reversed(cur_sents):
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if ov_l + estimate_tokens(os) < overlap:
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ov_s.insert(0, os); ov_l += estimate_tokens(os)
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else: break
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cur_sents = list(ov_s); cur_sents.append(s); sub_len = ov_l + slen
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else: cur_sents.append(s); sub_len += slen
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if cur_sents: _add_to_chunks(" ".join(cur_sents), main_title, main_path)
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buf = []; cur_tokens = 0
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for b in blocks:
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b_tokens = estimate_tokens(b.text)
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# Prüfung auf Split-Trigger (Überschriften)
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is_split_trigger = False
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if b.kind == "heading":
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if b.level < split_level:
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is_split_trigger = True
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elif b.level == split_level:
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if strict or cur_tokens >= target:
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is_split_trigger = True
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if is_split_trigger:
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_flush() # Vorherigen Puffer leeren
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buf.append(b) # Neue Überschrift in den neuen Puffer aufnehmen
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cur_tokens = b_tokens
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else:
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# Atomarer Check: Wenn der neue Block den aktuellen Chunk sprengen würde
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if cur_tokens + b_tokens > max_tokens and buf:
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_flush() # Puffer leeren, Block 'b' wird Teil des nächsten Chunks
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buf.append(b)
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cur_tokens += b_tokens
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_flush() # Letzten Puffer leeren
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return chunks
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def strategy_sliding_window(blocks: List[RawBlock],
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config: Dict[str, Any],
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note_id: str,
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context_prefix: str = "") -> List[Chunk]:
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"""
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Standard Sliding Window mit Korrektur für Heading-Retention.
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"""
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target = config.get("target", 400)
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max_tokens = config.get("max", 600)
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overlap_val = config.get("overlap", (50, 80))
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overlap = sum(overlap_val) // 2 if isinstance(overlap_val, tuple) else overlap_val
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chunks: List[Chunk] = []
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buf: List[RawBlock] = []
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def _flush_window():
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nonlocal buf
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if not buf: return
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txt = "\n\n".join([b.text for b in buf])
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idx = len(chunks)
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win = f"{context_prefix}\n{txt}".strip() if context_prefix else txt
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chunks.append(Chunk(
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id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx,
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text=txt, window=win, token_count=estimate_tokens(txt),
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section_title=buf[0].section_title, section_path=buf[0].section_path,
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neighbors_prev=None, neighbors_next=None
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))
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buf = []
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for b in blocks:
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# Auch hier: Überschriften mitnehmen
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b_tokens = estimate_tokens(b.text)
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current_buf_tokens = estimate_tokens("\n\n".join([x.text for x in buf])) if buf else 0
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if current_buf_tokens + b_tokens >= target and buf:
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_flush_window()
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buf.append(b)
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_flush_window()
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return chunks |